A multiscale absorption and transit model for oral delivery of hydroxychloroquine: Pharmacokinetic modeling and intestinal concentration prediction to assess toxicity and drug-induced damage in healthy subjects

A quasi-3D model of the whole lung: airway extension to the tracheobronchial limit using the constrained constructive optimization and alveolar modeling, using a sac-trumpet model

Existing computational models used for simulating the flow and species transport in the human airways are zero-dimensional (0D) compartmental, three-dimensional (3D) computational fluid dynamics (CFD), or the recently developed quasi-3D (Q3D) models. Unlike compartmental models, the full CFD and Q3D models are physiologically and anatomically consistent in the mouth and the upper airways, since the starting point of these models is the mouth-lung surface geometry, typically created from computed tomography (CT) scans. However, the current resolution of CT scans limits the airway detection between the 3rd-4th and 7th-9th generations. Consequently, CFD and the Q3D models developed using these scans are generally limited to these generations. In this study, we developed a method to extend the conducting airways from the end of the truncated Q3D lung to the tracheobronchial (TB) limit. We grew the lung generations within the closed lung lobes using the modified constrained constructive optimization, creating an aerodynamically optimized network aiming to produce equal pressure at the distal ends of the terminal segments. This resulted in a TB volume and lateral area of ∼165 cc and ∼2000 cm², respectively. We created a "sac-trumpet" model at each of the TB outlets to represent the alveoli. The volumes of the airways and the individual alveolar generations match the anatomical values by design: with the functional residual capacity at 2611 cc. Lateral surface areas were scaled to match the physiological values. These generated Q3D whole lung models can be efficiently used for conducting multiple breathing cycles of drug transport and deposition simulations.

More skilled clinical management of COVID-19 patients modified mortality in an intermediate respiratory intensive care unit in Italy

BACKGROUND

Some studies investigated epidemiological and clinical features of laboratory-confirmed patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the virus causing coronavirus disease 2019 (COVID-19), but limited attention has been paid to the follow-up of hospitalized patients on the basis of clinical setting and the expertise of clinical management.

METHODS

In the present single-centered, retrospective, observational study, we reported findings from 87 consecutive laboratory-confirmed COVID-19 patients with moderate-to-severe acute respiratory syndrome hospitalized in an intermediate Respiratory Intensive Care Unit (RICU), subdividing the patients in two groups according to the admission date (before and after March 29, 2020).

RESULTS

With improved skills in the clinical management of COVID-19, we observed a significant lower mortality in the T2 group compared with the T1 group and a significantly difference in terms of mortality among the patients transferred in Intensive Care Unit (ICU) from our intermediate RICU (100% in T1 group vs. 33.3% in T2 group). The average length of stay in intermediate RICU of ICU-transferred patients who survived in T1 and T2 was significantly longer than those who died (who died 3.3 ± 2.8 days vs. who survived 6.4 ± 3.3 days).

T CONCLUSIONS

The present findings suggested that an intermediate level of hospital care may have the potential to modify survival in COVID-19 patients, particularly in the present phase of a more skilled clinical management of the pandemic.